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Highlights from Data Driven Fitting with MATLAB

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Data Driven Fitting with MATLAB

Richard Willey (view profile)

Demostration code and data sets for the "Data Driven Fitting with MATLAB" webinar.

File Information
Description

Data driven fitting allows you to generate a fit without specifying a parametric equation that describes the relationship between your variables.

Fitit.m is a simple function for data driven curve fitting.

FititDemo.m illustrates how to use fitit to generate a curve fit.

Load_Forecasting.m demonstrates building a short term electricity load (or price) forecasting system with MATLAB. Three non-linear regression models (Boosted Decision Trees, Bagged Decision Trees, and Neural Networks) are calibrated to forecast hourly day-ahead loads given temperature forecasts, holiday information and historical loads. The models are trained on hourly data from the NEPOOL region (courtesy ISO New England) from 2004 to 2007 and tested on out-of-sample data from 2008.

Acknowledgements

This file inspired Data Driven Fitting Com Matlab.

Required Products Curve Fitting Toolbox
Neural Network Toolbox
Statistics Toolbox
MATLAB release MATLAB 7.12 (R2011a)
05 Dec 2014 Jim O'Doherty

Jim O'Doherty (view profile)

Anyone using this "out of the box" should change the line:

cp = cvpartition(100,'k',10);

to

cp = cvpartition(length(X),'k',10);

Comment only
03 Aug 2013 Benjamin

Benjamin (view profile)

how to change the row of data to fit the number of partition in the function cross validation?

Comment only
14 Aug 2012 Gwen Weng

Gwen Weng (view profile)

It requires the data to be dense and not have large gaps.

Comment only
06 Aug 2012 Boxiang

Boxiang (view profile)

The author of this file failed to mention that the number of row of the data to be fit must equals to the number of partition 'N' in the function corss validation. The users have to change it themselves.